code: def patch_env_manager():
      with mock.patch(
          "mlflow.recipes.steps.predict._ENV_MANAGER", "local"
      ):
          yield
  
imports: import os
  import tempfile
  from pathlib import Path
  from unittest import mock
  import pandas
  import pytest
  from pyspark.sql import SparkSession
  from sklearn.datasets import load_diabetes
  import mlflow
  from mlflow.exceptions import MlflowException
  from mlflow.recipes.artifacts import RegisteredModelVersionInfo
  from mlflow.recipes.steps.predict import _INPUT_FILE_NAME, _SCORED_OUTPUT_FILE_NAME, PredictStep
  from mlflow.recipes.steps.register import _REGISTERED_MV_INFO_FILE
  from mlflow.recipes.utils import _RECIPE_CONFIG_FILE_NAME
  from mlflow.utils.file_utils import read_yaml
  from tests.recipes.helper_functions import get_random_id, train_and_log_model, train_log_and_register_model
label_desc: Use image node_id 2 for calling a global function with example usage: patch_env_manager() without return types